{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Grade-derived R\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/grade-derived_R.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "054c70be81094d7783145594f70bf166",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0b377829e44147b7b1fc98361a6b1bbb",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grade-derived R: {1: 0.028059334206172126, 2: 0.5681181118431688, 3: 0.9665807730080513, 4: 0.9999195971791759}\n"
     ]
    }
   ],
   "source": [
    "from scipy.optimize import curve_fit\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "dataset['y'] = dataset['r'].map({1: 0, 2: 1, 3: 1, 4: 1})\n",
    "\n",
    "dataset['lapse'] = dataset['r_history'].str.count('1')\n",
    "grade_r_matrix = dataset.groupby(by=[\"delta_t\", \"i\", \"lapse\"]).agg({'y': ['count', 'mean'], 'r': 'mean'}).reset_index()\n",
    "grade_r_matrix.sort_values(by=[('r', 'mean')], inplace=True, ignore_index=True)\n",
    "grade_means = grade_r_matrix['r']['mean']\n",
    "r_means = grade_r_matrix['y']['mean']\n",
    "count = grade_r_matrix['y']['count']\n",
    "\n",
    "def func(x, a, b, c, d):\n",
    "    return np.clip(np.nan_to_num(1 - a * np.exp(-b*np.power((x+d), c))), a_min=0, a_max=1)\n",
    "\n",
    "params, covs = curve_fit(func, grade_means, r_means, bounds=((0.01, 0.01, 0.01, -4), (10, 5, 5, 4)), sigma=1/np.sqrt(count))\n",
    "plt.plot(grade_means, r_means, label='Exact')\n",
    "plt.plot(grade_means, func(grade_means, *params), label='Weighted fit')\n",
    "count_percent = np.array([x/sum(count) for x in count])\n",
    "plt.scatter(grade_means, r_means, s=count_percent * 1000, alpha=0.5)\n",
    "plt.legend(loc='upper right', fancybox=True, shadow=False)\n",
    "plt.grid(True)\n",
    "plt.xlabel('Grade mean')\n",
    "plt.ylabel('Recall mean')\n",
    "plt.show()\n",
    "\n",
    "grade_derived_r = dict(zip([1, 2, 3, 4], func(np.array([1, 2, 3, 4]), *params)))\n",
    "print(\"Grade-derived R: \" + str(grade_derived_r))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1, 0.5, 0.5, 0.5, 0.5]\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "        self.r_grade = torch.zeros(4)\n",
    "        for i in range(4):\n",
    "            if i+1 in grade_derived_r:\n",
    "                self.r_grade[i] = grade_derived_r[i+1]\n",
    "\n",
    "    def stability_after_success(self, s: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = s * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(s, self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1))\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, s: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * torch.pow(\n",
    "            s, self.w[11]) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r_theoretical = torch.exp(np.log(0.9) * X[:,0] / state[:,0])\n",
    "            keys = torch.tensor([1, 2, 3, 4])\n",
    "            keys = keys.view(1, -1).expand(X[:,1].long().size(0), -1)\n",
    "            index = (X[:,1].long().unsqueeze(1) == keys).nonzero(as_tuple=True)\n",
    "            r_grade = r_theoretical.clone()\n",
    "            r_grade[index[0]] = self.r_grade[index[1]]\n",
    "            weights = torch.zeros_like(r_grade)\n",
    "            weights[index[0]] = self.w[13+index[1]]\n",
    "            r_w = weights * r_grade + (1 - weights) * r_theoretical\n",
    "            r_w = r_w.clamp(0.0001, 0.9999)\n",
    "            s_w = state[:,0] * torch.log(r_theoretical.clamp(0.0001, 0.9999)) / torch.log(r_w)\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(s_w, new_d, r_w), self.stability_after_failure(s_w, new_d, r_w))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            w[13] = w[13].clamp(0, 1)\n",
    "            w[14] = w[14].clamp(0, 1)\n",
    "            w[15] = w[15].clamp(0, 1)\n",
    "            w[16] = w[16].clamp(0, 1)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='sum')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels)/len(self.train_set)\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = torch.exp(np.log(0.9) * delta_ts / stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels)/len(self.test_set)\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ea6859eed6874bfd8fc0a570edbbddab",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3343\n",
      "Loss in testset: 0.3132\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "be22752cc37f493b92ca96feee8df001",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2588, 1.8518, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.5, 0.5, 0.5, 0.5]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5019eb5e96fd48e396db04ae7b32ebe3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3328\n",
      "Loss in testset: 0.3115\n",
      "iteration: 15360\n",
      "w: [1.2327, 2.0554, 5.2042, -1.2942, -1.2014, 0.05, 1.4742, -0.1829, 0.8973, 2.0689, -0.1646, 0.2745, 0.9893, 0.6316, 1.0, 0.3193, 0.7855]\n",
      "iteration: 30720\n",
      "w: [1.2313, 2.0664, 5.2299, -1.7934, -1.4664, 0.05, 1.5862, -0.15, 0.9697, 2.1036, -0.1616, 0.2545, 0.9141, 0.6161, 1.0, 0.043, 0.4943]\n",
      "iteration: 46080\n",
      "w: [1.2312, 2.067, 5.1516, -1.8376, -1.5644, 0.05, 1.5936, -0.1948, 0.9585, 2.1429, -0.1437, 0.3398, 0.9077, 0.7169, 1.0, 0.0014, 0.6308]\n",
      "Loss in trainset: 0.3153\n",
      "Loss in testset: 0.2963\n",
      "iteration: 60984\n",
      "w: [1.2312, 2.067, 5.1793, -1.9446, -1.638, 0.05, 1.5596, -0.2458, 0.9021, 2.123, -0.173, 0.2738, 0.8749, 0.7329, 1.0, 0.0, 0.6233]\n",
      "iteration: 76344\n",
      "w: [1.2312, 2.067, 5.0494, -1.8957, -1.6257, 0.05, 1.6149, -0.1895, 0.9322, 2.1504, -0.1489, 0.1302, 0.8984, 0.7278, 1.0, 0.0, 0.6183]\n",
      "iteration: 91704\n",
      "w: [1.2312, 2.067, 5.1071, -1.9954, -1.6983, 0.05, 1.6053, -0.2261, 0.9084, 2.1768, -0.1305, 0.2179, 0.9165, 0.8582, 1.0, 0.0011, 0.6973]\n",
      "Loss in trainset: 0.3146\n",
      "Loss in testset: 0.2956\n",
      "iteration: 106608\n",
      "w: [1.2312, 2.067, 5.0352, -1.9677, -1.6413, 0.05, 1.6234, -0.2152, 0.9129, 2.147, -0.1657, 0.324, 0.8748, 0.9246, 1.0, 0.0, 0.5974]\n",
      "iteration: 121968\n",
      "w: [1.2312, 2.067, 5.0159, -1.9558, -1.6365, 0.05, 1.6282, -0.2141, 0.9113, 2.1856, -0.1278, 0.2708, 0.9196, 0.8445, 1.0, 0.0, 0.5926]\n",
      "iteration: 137328\n",
      "w: [1.2312, 2.067, 5.0161, -1.9695, -1.6426, 0.05, 1.6254, -0.2045, 0.9034, 2.1837, -0.1306, 0.2916, 0.9172, 0.8431, 1.0, 0.0, 0.597]\n",
      "iteration: 152688\n",
      "w: [1.2312, 2.067, 5.0161, -1.9692, -1.6427, 0.05, 1.6207, -0.2105, 0.8983, 2.1781, -0.1365, 0.2897, 0.9108, 0.8455, 1.0, 0.0, 0.5922]\n",
      "Loss in trainset: 0.3145\n",
      "Loss in testset: 0.2955\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3207\n",
      "Loss in testset: 0.3400\n"
     ]
    },
    {
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      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
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      "w: [2.0143, 2.047, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.5, 0.5, 0.5, 0.5]\n"
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      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
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     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3185\n",
      "Loss in testset: 0.3401\n",
      "iteration: 15360\n",
      "w: [2.1098, 2.1547, 5.1478, -1.4793, -1.2025, 0.05, 1.5255, -0.1528, 0.9601, 2.003, -0.2331, 0.3985, 0.9216, 0.2991, 0.7889, 0.3691, 0.8791]\n",
      "iteration: 30720\n",
      "w: [2.1147, 2.1603, 5.1936, -1.8074, -1.5136, 0.05, 1.5661, -0.21, 1.0082, 2.0603, -0.1983, 0.4024, 0.887, 0.184, 1.0, 0.1485, 0.6101]\n",
      "iteration: 46080\n",
      "w: [2.1149, 2.1605, 5.0829, -1.9943, -1.4963, 0.05, 1.5509, -0.2026, 0.9757, 2.0827, -0.1893, 0.2802, 0.8425, 0.1051, 1.0, 0.0278, 0.6026]\n",
      "Loss in trainset: 0.3023\n",
      "Loss in testset: 0.3220\n",
      "iteration: 60942\n",
      "w: [2.1149, 2.1605, 5.0943, -1.9301, -1.6699, 0.0633, 1.4869, -0.2307, 0.8985, 2.1288, -0.1572, 0.2931, 0.8429, 0.3011, 1.0, 0.0372, 0.5988]\n",
      "iteration: 76302\n",
      "w: [2.1149, 2.1605, 5.0127, -1.936, -1.6312, 0.05, 1.5131, -0.2438, 0.923, 2.1692, -0.1224, 0.3312, 0.8326, 0.3408, 1.0, 0.0, 0.5874]\n",
      "iteration: 91662\n",
      "w: [2.1149, 2.1605, 4.8574, -1.85, -1.5548, 0.05, 1.5834, -0.1999, 0.9803, 2.1488, -0.1486, 0.2839, 0.773, 0.3312, 1.0, 0.0099, 0.5821]\n",
      "Loss in trainset: 0.3014\n",
      "Loss in testset: 0.3216\n",
      "iteration: 106524\n",
      "w: [2.1149, 2.1605, 4.8753, -1.8993, -1.5573, 0.05, 1.5432, -0.2477, 0.9293, 2.1719, -0.1262, 0.2784, 0.7782, 0.312, 1.0, 0.0195, 0.5782]\n",
      "iteration: 121884\n",
      "w: [2.1149, 2.1605, 4.8807, -1.9438, -1.5853, 0.05, 1.5612, -0.2262, 0.9395, 2.1844, -0.1145, 0.2685, 0.7734, 0.2986, 1.0, 0.0248, 0.5799]\n",
      "iteration: 137244\n",
      "w: [2.1149, 2.1605, 4.8928, -1.9617, -1.5999, 0.05, 1.5532, -0.2297, 0.9281, 2.1972, -0.1022, 0.283, 0.7814, 0.2931, 1.0, 0.0224, 0.5772]\n",
      "iteration: 152604\n",
      "w: [2.1149, 2.1605, 4.8921, -1.9613, -1.6022, 0.05, 1.5539, -0.232, 0.9282, 2.1945, -0.1051, 0.2817, 0.7777, 0.2934, 1.0, 0.0182, 0.5772]\n",
      "Loss in trainset: 0.3014\n",
      "Loss in testset: 0.3215\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3261\n",
      "Loss in testset: 0.3287\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5d6a7a7c6f11439ca1c7823506cc9763",
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      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
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    },
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     "output_type": "stream",
     "text": [
      "w: [1.2804, 1.8287, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0, 0.5, 0.5, 0.5, 0.5]\n"
     ]
    },
    {
     "data": {
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       "model_id": "9369eca20a5d420d97c5bf7b8c874a3e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3248\n",
      "Loss in testset: 0.3265\n",
      "iteration: 15360\n",
      "w: [1.2103, 1.9125, 5.1553, -1.3847, -1.2626, 0.05, 1.4829, -0.2186, 0.9243, 2.0387, -0.1621, 0.2831, 0.981, 0.6093, 0.958, 0.3371, 0.5952]\n",
      "iteration: 30720\n",
      "w: [1.2066, 1.9168, 5.161, -1.6933, -1.5204, 0.05, 1.5224, -0.1974, 0.9623, 2.0582, -0.1675, 0.2826, 0.873, 0.8953, 1.0, 0.0824, 0.4732]\n",
      "iteration: 46080\n",
      "w: [1.2065, 1.917, 5.0463, -1.9161, -1.4511, 0.05, 1.5324, -0.1737, 0.9432, 2.1101, -0.1368, 0.218, 0.9178, 0.8655, 1.0, 0.0, 0.4878]\n",
      "Loss in trainset: 0.3080\n",
      "Loss in testset: 0.3093\n",
      "iteration: 60966\n",
      "w: [1.2065, 1.917, 4.9457, -1.7092, -1.5146, 0.05, 1.5208, -0.2165, 0.909, 2.1698, -0.1021, 0.3093, 0.9719, 0.9757, 1.0, 0.0436, 0.6187]\n",
      "iteration: 76326\n",
      "w: [1.2065, 1.917, 4.8538, -1.7122, -1.4626, 0.05, 1.5086, -0.2198, 0.8787, 2.139, -0.1432, 0.2026, 0.937, 0.7703, 1.0, 0.0, 0.5131]\n",
      "iteration: 91686\n",
      "w: [1.2065, 1.917, 4.862, -1.8058, -1.5488, 0.05, 1.5486, -0.1546, 0.8986, 2.1689, -0.1159, 0.24, 0.9554, 0.7725, 1.0, 0.0, 0.4574]\n",
      "Loss in trainset: 0.3076\n",
      "Loss in testset: 0.3091\n",
      "iteration: 106572\n",
      "w: [1.2065, 1.917, 4.872, -1.847, -1.5939, 0.0563, 1.5671, -0.1782, 0.91, 2.1325, -0.1564, 0.2441, 0.9122, 0.7737, 1.0, 0.0276, 0.4438]\n",
      "iteration: 121932\n",
      "w: [1.2065, 1.917, 4.8654, -1.8471, -1.6148, 0.05, 1.5672, -0.2031, 0.9045, 2.1442, -0.1461, 0.2623, 0.9199, 0.7843, 1.0, 0.0128, 0.4177]\n",
      "iteration: 137292\n",
      "w: [1.2065, 1.917, 4.8918, -1.88, -1.6445, 0.05, 1.5516, -0.2124, 0.8862, 2.1547, -0.136, 0.2686, 0.9292, 0.7891, 1.0, 0.0056, 0.4215]\n",
      "iteration: 152652\n",
      "w: [1.2065, 1.917, 4.8913, -1.8818, -1.6466, 0.05, 1.5517, -0.2118, 0.8857, 2.1552, -0.1357, 0.2693, 0.9295, 0.7898, 1.0, 0.0019, 0.4235]\n",
      "Loss in trainset: 0.3075\n",
      "Loss in testset: 0.3091\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.5175, 2.0482, 4.9331, -1.9374, -1.6305, 0.05, 1.5755, -0.2181, 0.9041, 2.1759, -0.1258, 0.2802, 0.8726, 0.6429, 1.0, 0.0067, 0.531]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,2d,4d,7d,13d,23d,1.3m,2.2m,3.5m,5.6m,8.6m\n",
      "difficulty history: 0,8.8,8.6,8.4,8.3,8.1,7.9,7.8,7.6,7.5,7.4\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,9d,20d,1.4m,2.6m,4.8m,8.2m,1.1y,1.8y,2.7y\n",
      "difficulty history: 0,6.9,6.8,6.7,6.6,6.5,6.4,6.4,6.3,6.2,6.2\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,17d,1.4m,3.2m,6.4m,12.1m,1.8y,3.0y,4.8y,7.4y\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,26d,2.4m,5.7m,1.0y,2.0y,3.6y,6.2y,10.0y,15.7y\n",
      "difficulty history: 0,3.0,3.1,3.2,3.3,3.4,3.4,3.5,3.6,3.6,3.7\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(round(float(np.log(requestRetention)/np.log(0.9) * states[0])), 1)\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6139, 4.9331])\n",
      "tensor([17.0501,  4.9331])\n",
      "tensor([42.5160,  4.9331])\n",
      "tensor([95.3202,  4.9331])\n",
      "tensor([193.2330,   4.9331])\n",
      "tensor([6.7811, 8.0311])\n",
      "tensor([ 2.6047, 10.0000])\n",
      "tensor([4.0102, 9.7467])\n",
      "tensor([6.0459, 9.5060])\n",
      "tensor([9.2640, 9.2773])\n",
      "tensor([14.2169,  9.0601])\n",
      "tensor([21.9790,  8.8538])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,17,43,95,193,7,3,4,6,9,14,22\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,8.0,10.0,9.7,9.5,9.3,9.1,8.9\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1,round(float(np.log(requestRetention)/np.log(0.9) * states[0])))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3269, loss after: 0.3078, improvement: 0.0192\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9327\n",
      "RMSE: 0.0188\n",
      "[0.0624     0.93151372]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.1871\n",
      "RMSE: 0.0505\n",
      "[0.33446291 0.60698106]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: -0.0582\n",
      "RMSE: 0.0627\n",
      "[0.23128012 0.68428131]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9366\n",
      "RMSE: 0.0196\n",
      "[0.00520221 1.004197  ]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: 0.4471\n",
      "RMSE: 0.0203\n",
      "[0.34215345 0.65114928]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row3_col3 {\n",
       "  background-color: #a1a1ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_0d077_row3_col4 {\n",
       "  background-color: #ff7979;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_0d077_row3_col5, #T_0d077_row8_col1, #T_0d077_row9_col0, #T_0d077_row9_col1, #T_0d077_row10_col1, #T_0d077_row13_col1 {\n",
       "  background-color: #d1d1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row3_col6 {\n",
       "  background-color: #e9e9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row3_col7, #T_0d077_row12_col6 {\n",
       "  background-color: #f9f9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row4_col3, #T_0d077_row4_col6, #T_0d077_row5_col6 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row4_col4 {\n",
       "  background-color: #ffdddd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row4_col7, #T_0d077_row8_col2, #T_0d077_row8_col5, #T_0d077_row12_col5 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row5_col2, #T_0d077_row7_col1, #T_0d077_row14_col3 {\n",
       "  background-color: #e5e5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row5_col3 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row5_col5, #T_0d077_row11_col1, #T_0d077_row14_col1 {\n",
       "  background-color: #bdbdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row5_col7 {\n",
       "  background-color: #fff9f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row6_col1, #T_0d077_row6_col2, #T_0d077_row12_col1 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row6_col3 {\n",
       "  background-color: #b1b1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row6_col5, #T_0d077_row12_col2 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row6_col6 {\n",
       "  background-color: #ededff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row6_col7 {\n",
       "  background-color: #ffe1e1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row7_col2 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row7_col3 {\n",
       "  background-color: #fffdfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row7_col6 {\n",
       "  background-color: #ffe5e5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row7_col7, #T_0d077_row13_col3 {\n",
       "  background-color: #ffa5a5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row8_col6 {\n",
       "  background-color: #ffa9a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row8_col7 {\n",
       "  background-color: #ff6969;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_0d077_row9_col2 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row9_col5 {\n",
       "  background-color: #ff9999;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row9_col6 {\n",
       "  background-color: #ffb1b1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row9_col7 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row10_col3 {\n",
       "  background-color: #ffb5b5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row10_col4 {\n",
       "  background-color: #ff7171;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_0d077_row10_col5 {\n",
       "  background-color: #ffd1d1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row10_col6 {\n",
       "  background-color: #ff6d6d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_0d077_row10_col7 {\n",
       "  background-color: #ff7d7d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_0d077_row11_col0 {\n",
       "  background-color: #b9b9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row11_col3, #T_0d077_row11_col4 {\n",
       "  background-color: #ffa1a1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row12_col3 {\n",
       "  background-color: #ff8d8d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row13_col2, #T_0d077_row14_col2, #T_0d077_row15_col2 {\n",
       "  background-color: #a5a5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_0d077_row13_col5 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_0d077\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_0d077_level0_col0\" class=\"col_heading level0 col0\" >2</th>\n",
       "      <th id=\"T_0d077_level0_col1\" class=\"col_heading level0 col1\" >3</th>\n",
       "      <th id=\"T_0d077_level0_col2\" class=\"col_heading level0 col2\" >5</th>\n",
       "      <th id=\"T_0d077_level0_col3\" class=\"col_heading level0 col3\" >6</th>\n",
       "      <th id=\"T_0d077_level0_col4\" class=\"col_heading level0 col4\" >7</th>\n",
       "      <th id=\"T_0d077_level0_col5\" class=\"col_heading level0 col5\" >8</th>\n",
       "      <th id=\"T_0d077_level0_col6\" class=\"col_heading level0 col6\" >9</th>\n",
       "      <th id=\"T_0d077_level0_col7\" class=\"col_heading level0 col7\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row0\" class=\"row_heading level0 row0\" >0.710000</th>\n",
       "      <td id=\"T_0d077_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_0d077_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_0d077_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_0d077_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_0d077_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_0d077_row0_col5\" class=\"data row0 col5\" ></td>\n",
       "      <td id=\"T_0d077_row0_col6\" class=\"data row0 col6\" ></td>\n",
       "      <td id=\"T_0d077_row0_col7\" class=\"data row0 col7\" >-10.04%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row1\" class=\"row_heading level0 row1\" >1.400000</th>\n",
       "      <td id=\"T_0d077_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_0d077_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_0d077_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_0d077_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_0d077_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_0d077_row1_col5\" class=\"data row1 col5\" ></td>\n",
       "      <td id=\"T_0d077_row1_col6\" class=\"data row1 col6\" >2.63%</td>\n",
       "      <td id=\"T_0d077_row1_col7\" class=\"data row1 col7\" >0.88%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row2\" class=\"row_heading level0 row2\" >1.960000</th>\n",
       "      <td id=\"T_0d077_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_0d077_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_0d077_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_0d077_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_0d077_row2_col4\" class=\"data row2 col4\" ></td>\n",
       "      <td id=\"T_0d077_row2_col5\" class=\"data row2 col5\" ></td>\n",
       "      <td id=\"T_0d077_row2_col6\" class=\"data row2 col6\" >-4.18%</td>\n",
       "      <td id=\"T_0d077_row2_col7\" class=\"data row2 col7\" >-0.07%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row3\" class=\"row_heading level0 row3\" >2.740000</th>\n",
       "      <td id=\"T_0d077_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_0d077_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_0d077_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_0d077_row3_col3\" class=\"data row3 col3\" >-3.68%</td>\n",
       "      <td id=\"T_0d077_row3_col4\" class=\"data row3 col4\" >5.21%</td>\n",
       "      <td id=\"T_0d077_row3_col5\" class=\"data row3 col5\" >-1.73%</td>\n",
       "      <td id=\"T_0d077_row3_col6\" class=\"data row3 col6\" >-0.78%</td>\n",
       "      <td id=\"T_0d077_row3_col7\" class=\"data row3 col7\" >-0.29%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row4\" class=\"row_heading level0 row4\" >3.840000</th>\n",
       "      <td id=\"T_0d077_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_0d077_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_0d077_row4_col2\" class=\"data row4 col2\" ></td>\n",
       "      <td id=\"T_0d077_row4_col3\" class=\"data row4 col3\" >-2.22%</td>\n",
       "      <td id=\"T_0d077_row4_col4\" class=\"data row4 col4\" >1.34%</td>\n",
       "      <td id=\"T_0d077_row4_col5\" class=\"data row4 col5\" >-0.13%</td>\n",
       "      <td id=\"T_0d077_row4_col6\" class=\"data row4 col6\" >-2.22%</td>\n",
       "      <td id=\"T_0d077_row4_col7\" class=\"data row4 col7\" >0.68%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row5\" class=\"row_heading level0 row5\" >5.380000</th>\n",
       "      <td id=\"T_0d077_row5_col0\" class=\"data row5 col0\" ></td>\n",
       "      <td id=\"T_0d077_row5_col1\" class=\"data row5 col1\" ></td>\n",
       "      <td id=\"T_0d077_row5_col2\" class=\"data row5 col2\" >-0.99%</td>\n",
       "      <td id=\"T_0d077_row5_col3\" class=\"data row5 col3\" >-2.17%</td>\n",
       "      <td id=\"T_0d077_row5_col4\" class=\"data row5 col4\" ></td>\n",
       "      <td id=\"T_0d077_row5_col5\" class=\"data row5 col5\" >-2.53%</td>\n",
       "      <td id=\"T_0d077_row5_col6\" class=\"data row5 col6\" >-2.27%</td>\n",
       "      <td id=\"T_0d077_row5_col7\" class=\"data row5 col7\" >0.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row6\" class=\"row_heading level0 row6\" >7.530000</th>\n",
       "      <td id=\"T_0d077_row6_col0\" class=\"data row6 col0\" ></td>\n",
       "      <td id=\"T_0d077_row6_col1\" class=\"data row6 col1\" >-1.32%</td>\n",
       "      <td id=\"T_0d077_row6_col2\" class=\"data row6 col2\" >-1.27%</td>\n",
       "      <td id=\"T_0d077_row6_col3\" class=\"data row6 col3\" >-2.98%</td>\n",
       "      <td id=\"T_0d077_row6_col4\" class=\"data row6 col4\" ></td>\n",
       "      <td id=\"T_0d077_row6_col5\" class=\"data row6 col5\" >-0.39%</td>\n",
       "      <td id=\"T_0d077_row6_col6\" class=\"data row6 col6\" >-0.68%</td>\n",
       "      <td id=\"T_0d077_row6_col7\" class=\"data row6 col7\" >1.23%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row7\" class=\"row_heading level0 row7\" >10.540000</th>\n",
       "      <td id=\"T_0d077_row7_col0\" class=\"data row7 col0\" ></td>\n",
       "      <td id=\"T_0d077_row7_col1\" class=\"data row7 col1\" >-1.08%</td>\n",
       "      <td id=\"T_0d077_row7_col2\" class=\"data row7 col2\" >-2.03%</td>\n",
       "      <td id=\"T_0d077_row7_col3\" class=\"data row7 col3\" >0.09%</td>\n",
       "      <td id=\"T_0d077_row7_col4\" class=\"data row7 col4\" ></td>\n",
       "      <td id=\"T_0d077_row7_col5\" class=\"data row7 col5\" >0.92%</td>\n",
       "      <td id=\"T_0d077_row7_col6\" class=\"data row7 col6\" >1.05%</td>\n",
       "      <td id=\"T_0d077_row7_col7\" class=\"data row7 col7\" >3.52%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row8\" class=\"row_heading level0 row8\" >14.760000</th>\n",
       "      <td id=\"T_0d077_row8_col0\" class=\"data row8 col0\" >0.93%</td>\n",
       "      <td id=\"T_0d077_row8_col1\" class=\"data row8 col1\" >-1.80%</td>\n",
       "      <td id=\"T_0d077_row8_col2\" class=\"data row8 col2\" >0.65%</td>\n",
       "      <td id=\"T_0d077_row8_col3\" class=\"data row8 col3\" >0.90%</td>\n",
       "      <td id=\"T_0d077_row8_col4\" class=\"data row8 col4\" ></td>\n",
       "      <td id=\"T_0d077_row8_col5\" class=\"data row8 col5\" >0.68%</td>\n",
       "      <td id=\"T_0d077_row8_col6\" class=\"data row8 col6\" >3.28%</td>\n",
       "      <td id=\"T_0d077_row8_col7\" class=\"data row8 col7\" >5.89%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row9\" class=\"row_heading level0 row9\" >20.660000</th>\n",
       "      <td id=\"T_0d077_row9_col0\" class=\"data row9 col0\" >-1.78%</td>\n",
       "      <td id=\"T_0d077_row9_col1\" class=\"data row9 col1\" >-1.72%</td>\n",
       "      <td id=\"T_0d077_row9_col2\" class=\"data row9 col2\" >-1.43%</td>\n",
       "      <td id=\"T_0d077_row9_col3\" class=\"data row9 col3\" >-0.15%</td>\n",
       "      <td id=\"T_0d077_row9_col4\" class=\"data row9 col4\" >0.89%</td>\n",
       "      <td id=\"T_0d077_row9_col5\" class=\"data row9 col5\" >3.99%</td>\n",
       "      <td id=\"T_0d077_row9_col6\" class=\"data row9 col6\" >3.03%</td>\n",
       "      <td id=\"T_0d077_row9_col7\" class=\"data row9 col7\" >1.58%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row10\" class=\"row_heading level0 row10\" >28.930000</th>\n",
       "      <td id=\"T_0d077_row10_col0\" class=\"data row10 col0\" ></td>\n",
       "      <td id=\"T_0d077_row10_col1\" class=\"data row10 col1\" >-1.73%</td>\n",
       "      <td id=\"T_0d077_row10_col2\" class=\"data row10 col2\" >0.89%</td>\n",
       "      <td id=\"T_0d077_row10_col3\" class=\"data row10 col3\" >2.88%</td>\n",
       "      <td id=\"T_0d077_row10_col4\" class=\"data row10 col4\" >5.58%</td>\n",
       "      <td id=\"T_0d077_row10_col5\" class=\"data row10 col5\" >1.77%</td>\n",
       "      <td id=\"T_0d077_row10_col6\" class=\"data row10 col6\" >5.67%</td>\n",
       "      <td id=\"T_0d077_row10_col7\" class=\"data row10 col7\" >5.07%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row11\" class=\"row_heading level0 row11\" >40.500000</th>\n",
       "      <td id=\"T_0d077_row11_col0\" class=\"data row11 col0\" >-2.73%</td>\n",
       "      <td id=\"T_0d077_row11_col1\" class=\"data row11 col1\" >-2.60%</td>\n",
       "      <td id=\"T_0d077_row11_col2\" class=\"data row11 col2\" >-0.07%</td>\n",
       "      <td id=\"T_0d077_row11_col3\" class=\"data row11 col3\" >3.68%</td>\n",
       "      <td id=\"T_0d077_row11_col4\" class=\"data row11 col4\" >3.63%</td>\n",
       "      <td id=\"T_0d077_row11_col5\" class=\"data row11 col5\" >-0.06%</td>\n",
       "      <td id=\"T_0d077_row11_col6\" class=\"data row11 col6\" >0.79%</td>\n",
       "      <td id=\"T_0d077_row11_col7\" class=\"data row11 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row12\" class=\"row_heading level0 row12\" >56.690000</th>\n",
       "      <td id=\"T_0d077_row12_col0\" class=\"data row12 col0\" ></td>\n",
       "      <td id=\"T_0d077_row12_col1\" class=\"data row12 col1\" >-1.38%</td>\n",
       "      <td id=\"T_0d077_row12_col2\" class=\"data row12 col2\" >-0.37%</td>\n",
       "      <td id=\"T_0d077_row12_col3\" class=\"data row12 col3\" >4.48%</td>\n",
       "      <td id=\"T_0d077_row12_col4\" class=\"data row12 col4\" ></td>\n",
       "      <td id=\"T_0d077_row12_col5\" class=\"data row12 col5\" >0.76%</td>\n",
       "      <td id=\"T_0d077_row12_col6\" class=\"data row12 col6\" >-0.22%</td>\n",
       "      <td id=\"T_0d077_row12_col7\" class=\"data row12 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row13\" class=\"row_heading level0 row13\" >79.370000</th>\n",
       "      <td id=\"T_0d077_row13_col0\" class=\"data row13 col0\" ></td>\n",
       "      <td id=\"T_0d077_row13_col1\" class=\"data row13 col1\" >-1.73%</td>\n",
       "      <td id=\"T_0d077_row13_col2\" class=\"data row13 col2\" >-3.55%</td>\n",
       "      <td id=\"T_0d077_row13_col3\" class=\"data row13 col3\" >3.58%</td>\n",
       "      <td id=\"T_0d077_row13_col4\" class=\"data row13 col4\" ></td>\n",
       "      <td id=\"T_0d077_row13_col5\" class=\"data row13 col5\" >0.60%</td>\n",
       "      <td id=\"T_0d077_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "      <td id=\"T_0d077_row13_col7\" class=\"data row13 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row14\" class=\"row_heading level0 row14\" >111.120000</th>\n",
       "      <td id=\"T_0d077_row14_col0\" class=\"data row14 col0\" ></td>\n",
       "      <td id=\"T_0d077_row14_col1\" class=\"data row14 col1\" >-2.63%</td>\n",
       "      <td id=\"T_0d077_row14_col2\" class=\"data row14 col2\" >-3.55%</td>\n",
       "      <td id=\"T_0d077_row14_col3\" class=\"data row14 col3\" >-1.07%</td>\n",
       "      <td id=\"T_0d077_row14_col4\" class=\"data row14 col4\" ></td>\n",
       "      <td id=\"T_0d077_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_0d077_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "      <td id=\"T_0d077_row14_col7\" class=\"data row14 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_0d077_level0_row15\" class=\"row_heading level0 row15\" >155.570000</th>\n",
       "      <td id=\"T_0d077_row15_col0\" class=\"data row15 col0\" ></td>\n",
       "      <td id=\"T_0d077_row15_col1\" class=\"data row15 col1\" ></td>\n",
       "      <td id=\"T_0d077_row15_col2\" class=\"data row15 col2\" >-3.51%</td>\n",
       "      <td id=\"T_0d077_row15_col3\" class=\"data row15 col3\" ></td>\n",
       "      <td id=\"T_0d077_row15_col4\" class=\"data row15 col4\" ></td>\n",
       "      <td id=\"T_0d077_row15_col5\" class=\"data row15 col5\" ></td>\n",
       "      <td id=\"T_0d077_row15_col6\" class=\"data row15 col6\" ></td>\n",
       "      <td id=\"T_0d077_row15_col7\" class=\"data row15 col7\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2cd7c9820>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.04021710917230792\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0126\n",
      "Universal Metric of SM2: 0.0783\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
